Many modern research fields increasingly rely on collecting and analysing massive, often unstructured, and unwieldy datasets. Consequently, there is growing interest in machine learning and artificial intelligence applications that can harness this `data deluge'. This broad nontechnical overview provides a gentle introduction to machine learning with a specific focus on medical and biological applications. We explain the common types of machine learning algorithms and typical tasks that can be solved, illustrating the basics with concrete examples from healthcare. Lastly, we provide an outlook on open challenges, limitations, and potential impacts of machine-learning-powered medicine.
翻译:许多现代研究领域日益依赖收集和分析大规模、往往没有结构的和不灵巧的数据集,因此,人们越来越关注机器学习和人工智能应用,以便利用这种“数据大流”手段。这种广泛的非技术概览为机器学习提供了温和的介绍,具体侧重于医疗和生物应用。我们解释了机器学习的常见类型和可以解决的典型任务,用医疗保健的具体例子说明了基本原理。最后,我们提出了关于机器学习动力医学的公开挑战、局限性和潜在影响的前景。